Wavelength-routed optical backbone network planning under fuzzy environment

Network planning is an important design-step wherein various network resources are provisioned at different network locations. Traffic demand for all node pairs in the network is an important determining factor for network planning, and typically, a static traffic demand matrix consisting of long-term average traffic values for all node pairs is employed. However, assessment of traffic demand matrix may not be accurate (precise). In this paper, we propose an optimization framework to minimize traffic congestion in a wavelength-routed wavelength-division multiplexing WDM optical backbone network using such approximate traffic demands. Modeling such a network is constrained by limited network resources, and can be formulated in general as a fuzzy optimization problem. Moreover, decision maker might want to relax traffic congestion goal by a small margin in presence of approximate traffic demand matrix, so as to reach some aspiration level, rather missing the crisp target by a very small amount. We use the network planning model to minimize traffic congestion so as to achieve an aspiration level of traffic congestion. We use Zimmermann’s fuzzy programming technique to explore mixed integer linear programing based optimization model incorporating fuzzified constraints and objective function. All related constraints, such as traffic and lightpath routing, wavelength selection, restriction due to average propagation delay, lightpath degree and maximum hop count constraints are taken into consideration. Following the proposed model, under fuzzy environment, we implement reliable and efficient network planning and traffic provisioning, and estimate traffic congestion more accurately.